Interaction of fibre type, potentiation and fatigue in human knee extensor muscles
Bibliographic record
Abstract
AIM: To examine the effect of fibre type on potentiation and fatigue. METHODS: Young men (n = 4 per group) with a predominance of type I [61.4 +/- 6.9% (SD), group I (GI)] or type II [71.8 +/- 9.2%, group II (GII)] fibres in vastus lateralis, performed a fatigue protocol of sixteen 5-s maximal voluntary isometric contractions (MVCs) of the right knee extensors. Maximal twitches and corresponding muscle action potentials (M-waves) were evoked before the first MVC, during the 3-s rest period after each MVC and at intervals during the 5-min recovery period after the last MVC. RESULTS: Group II [49.3 +/- 2.6% (SE)] had a greater decrease in MVC force than GI (22.8 +/- 6.2%) during the fatigue protocol. Group II (126.4 +/- 13.6%) showed greater twitch force potentiation early in the fatigue protocol than GI (38.2 +/- 2.3%), but greater depression at the end (33.7 +/- 13.7% vs.17.4 +/- 3.4%). Twitch time-to-peak torque (TPT) and half relaxation time (HRT) initially decreased but then increased as the fatigue protocol progressed; GII had a greater increase in HRT. During a 5-min recovery period twitch force increased above the prefatigue level and remained so until the end of the recovery period; the pattern was similar in GI and GII. Twitch TPT and HRT remained elevated during recovery. M-wave area increased throughout the fatigue protocol and the first part of recovery before returning to baseline values in GII, whereas there were no significant changes in GI. The interaction between potentiation and fatigue was amplified in GII early in the fatigue protocol with concurrently greater twitch and M-wave potentiation, and greater MVC force decrease and HRT increase. Late in the protocol, GII had a greater decrease in twitch and MVC force combined with greater M-wave potentiation. CONCLUSION: It is concluded that fibre type distribution influences potentiation and fatigue of the twitch, and potentiation of the M-wave during fatiguing exercise.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".